# Copyright 2020 JD.com, Inc. Galileo Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================

import torch
import torch.nn.functional as F
from galileo.platform.export import export


def neg_cross_entropy(logits, negative_logits):
    sum_logits = F.logsigmoid(logits).sum(dim=-1)
    sum_negative_logits = F.logsigmoid(-negative_logits).sum(dim=-1)
    return -(sum_logits + sum_negative_logits).mean()


def multi_label_sm(labels, logits):
    criterion = torch.nn.MultiLabelSoftMarginLoss()
    return criterion(logits, labels).mean()


losses_dict = {k: v for k, v in globals().items() if callable(v)}


@export('galileo.pytorch')
def get_loss(name):
    assert name in losses_dict, f'not support loss {name}'
    return losses_dict[name]
